AI RESEARCH
Toward domain-specific machine translation and quality estimation systems
arXiv CS.AI
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ArXi:2603.24955v1 Announce Type: cross Machine Translation (MT) and Quality Estimation (QE) perform well in general domains but degrade under domain mismatch. This dissertation studies how to adapt MT and QE systems to specialized domains through a set of data-focused contributions. Chapter 2 presents a similarity-based data selection method for MT. Small, targeted in-domain subsets outperform much larger generic datasets and reach strong translation quality at lower computational cost. Chapter 3.